Add production-ready Virtual File System with intelligent Knowledge Layer: Core VFS Features: - Complete file system operations (read, write, mkdir, etc.) - Intelligent PathResolver with 4-layer caching system - Chunked storage for large files with real compression - Embedding generation for semantic operations - File relationships and metadata tracking - Import functionality from local filesystem Knowledge Layer Integration: - EventRecorder for complete file history and temporal coupling - SemanticVersioning with content-based change detection - PersistentEntitySystem for character/entity tracking across files - ConceptSystem for universal concept mapping and graphs - GitBridge for import/export between VFS and Git repositories Architecture: - KnowledgeAugmentation properly integrated into Brainy augmentation system - KnowledgeLayer wrapper provides real-time VFS operation interception - Background processing ensures VFS operations remain fast - All components use real Brainy embed() method for embeddings - Support for creative writing, coding projects, and project management Technical Implementation: - Fixed all stub/mock implementations with real working code - TypeScript compilation passes without errors - Comprehensive test suite demonstrating all features - Documentation covering architecture and usage patterns - Backwards compatible with existing Brainy functionality This enables scenarios like writing books with persistent characters, managing coding projects with concept tracking, and complete project coordination with intelligent file relationships.
505 lines
No EOL
14 KiB
Markdown
505 lines
No EOL
14 KiB
Markdown
# Knowledge Layer API Documentation 📚🧠
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## Overview
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The Knowledge Layer transforms Brainy's VFS from a simple filesystem into an intelligent knowledge system where files understand themselves, track their evolution, and maintain relationships across time.
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## Quick Start
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```typescript
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import { Brainy, VirtualFileSystem, KnowledgeAugmentation } from '@soulcraft/brainy'
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// Initialize Brainy with VFS
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const brain = new Brainy()
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await brain.init()
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const vfs = new VirtualFileSystem(brain)
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await vfs.init()
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// Enable Knowledge Layer
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const knowledge = new KnowledgeAugmentation({
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enabled: true,
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eventRecording: { enabled: true },
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semanticVersioning: { enabled: true, threshold: 0.3 },
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persistentEntities: { enabled: true, autoExtract: true },
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concepts: { enabled: true, autoLink: true },
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gitBridge: { enabled: true }
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})
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await knowledge.init({ brain, vfs })
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// Now your VFS has superpowers! 🚀
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```
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## Core Components
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### 1. Event Recording - Complete History Tracking
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Every file operation becomes a searchable event with full context.
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```typescript
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// Automatic event recording
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await vfs.writeFile('/project/README.md', 'Initial README')
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await vfs.writeFile('/project/README.md', 'Updated README')
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// Get complete history
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const history = await vfs.getHistory('/project/README.md')
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console.log(history)
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// [
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// { type: 'write', timestamp: 1234567890, content: Buffer('Updated README') },
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// { type: 'write', timestamp: 1234567880, content: Buffer('Initial README') }
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// ]
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// Time travel - reconstruct file at any point
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const pastContent = await vfs.reconstructAtTime('/project/README.md', 1234567885)
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console.log(pastContent.toString()) // "Initial README"
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// Get statistics
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const stats = await vfs.getStatistics('/project/README.md')
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console.log(stats)
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// {
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// totalEvents: 2,
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// totalWrites: 2,
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// totalBytes: 25,
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// authors: ['system'],
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// firstEvent: 1234567880,
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// lastEvent: 1234567890
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// }
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```
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### 2. Semantic Versioning - Only Version When Meaning Changes
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90% fewer versions than Git by only versioning when content meaning changes.
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```typescript
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// Automatic semantic versioning
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await vfs.writeFile('/code/api.js', 'function login() { /* v1 */ }')
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await vfs.writeFile('/code/api.js', 'function login() { /* v1 with comment */ }') // No new version
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await vfs.writeFile('/code/api.js', 'function login() { return authenticate() }') // New version!
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// Get versions (only meaningful ones)
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const versions = await vfs.getVersions('/code/api.js')
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console.log(versions.length) // 2 (not 3!)
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// Get specific version
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const v1Content = await vfs.getVersion('/code/api.js', versions[1].id)
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// Restore to previous version
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await vfs.restoreVersion('/code/api.js', versions[1].id)
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```
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### 3. Persistent Entities - Universal Characters
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Track entities that evolve across files and time. Not just story characters - APIs, customers, services, any evolving entity.
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```typescript
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// Create a persistent entity
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const apiEntityId = await vfs.createEntity({
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name: 'User API',
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type: 'api',
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aliases: ['UserService', 'UserAPI'],
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attributes: { version: '1.0', methods: ['get', 'post'] }
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})
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// Record appearance in a file
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await vfs.recordAppearance(
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apiEntityId,
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'/docs/api.md',
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'The User API provides endpoints for user management...'
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)
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// Find all appearances
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const appearances = await vfs.findEntityAppearances(apiEntityId)
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// Evolve the entity
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await vfs.evolveEntity(
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apiEntityId,
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{ attributes: { version: '2.0', methods: ['get', 'post', 'delete'] } },
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'/docs/changelog.md',
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'Added delete functionality'
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)
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// Get evolution timeline
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const { entity, timeline } = await vfs.getEntityEvolution(apiEntityId)
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console.log(timeline) // All changes over time
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```
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### 4. Universal Concepts - Ideas That Transcend Files
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Concepts exist independently and can be linked to multiple manifestations.
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```typescript
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// Create a universal concept
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const authConceptId = await vfs.createConcept({
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name: 'Authentication',
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domain: 'security',
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category: 'pattern',
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keywords: ['auth', 'login', 'security'],
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strength: 0.9,
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metadata: {}
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})
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// Link concepts together
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await vfs.linkConcept(authConceptId, otherConceptId, 'related', {
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strength: 0.8,
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context: 'Both are security-related patterns'
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})
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// Record manifestation
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await vfs.recordManifestation(
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authConceptId,
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'/src/auth.js',
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'class AuthService implements authentication...',
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'implementation'
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)
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// Find concept appearances
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const manifestations = await vfs.findConceptAppearances(authConceptId)
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// Get concept graph for visualization
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const graph = await vfs.getConceptGraph({ domain: 'security' })
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// { concepts: [...], links: [...] }
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```
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### 5. Git Bridge - Import/Export Without Dependencies
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Import any directory structure or export to Git-compatible format.
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```typescript
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// Import from any directory (not just Git repos)
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const stats = await vfs.importFromGit(
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'/path/to/project',
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'/imported-project',
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{
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preserveGitHistory: true,
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extractMetadata: true
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}
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)
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console.log(stats)
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// {
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// filesImported: 150,
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// eventsCreated: 75,
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// entitiesCreated: 12,
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// relationshipsCreated: 8
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// }
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// Export to Git format
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const gitRepo = await vfs.exportToGit(
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'/my-project',
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'/export/git-repo',
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{
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preserveMetadata: true,
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preserveRelationships: true,
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commitMessage: 'Export from Brainy VFS'
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}
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)
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```
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## Configuration Options
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### Knowledge Augmentation Config
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```typescript
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interface KnowledgeAugmentationConfig {
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enabled?: boolean // Master enable/disable (default: true)
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eventRecording?: {
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enabled?: boolean // Record all operations (default: true)
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pruneAfterDays?: number // Auto-prune old events (default: 90)
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compressEvents?: boolean // Compress event storage (default: false)
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}
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semanticVersioning?: {
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enabled?: boolean // Semantic versioning (default: true)
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threshold?: number // Semantic change threshold 0-1 (default: 0.3)
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maxVersions?: number // Max versions per file (default: 10)
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}
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persistentEntities?: {
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enabled?: boolean // Entity system (default: true)
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autoExtract?: boolean // Auto-extract from content (default: false)
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}
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concepts?: {
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enabled?: boolean // Concept system (default: true)
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autoLink?: boolean // Auto-link concepts (default: false)
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}
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gitBridge?: {
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enabled?: boolean // Git import/export (default: true)
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}
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}
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```
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### Component-Specific Configs
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```typescript
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// Event Recorder
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const eventRecorder = new EventRecorder(brain)
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// Semantic Versioning
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const versioning = new SemanticVersioning(brain, {
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threshold: 0.3, // Only version if >30% semantic change
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maxVersions: 10, // Keep max 10 versions per file
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minInterval: 60000 // Minimum 1 minute between versions
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})
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// Persistent Entities
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const entities = new PersistentEntitySystem(brain, {
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autoExtract: true, // Auto-extract entities
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similarityThreshold: 0.8, // Entity matching threshold
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maxAppearances: 100, // Max appearances per entity
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evolutionTracking: true // Track entity evolution
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})
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// Concepts
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const concepts = new ConceptSystem(brain, {
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autoLink: true, // Auto-link related concepts
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similarityThreshold: 0.7, // Concept similarity threshold
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maxManifestations: 1000, // Max manifestations per concept
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strengthDecay: 0.95 // Concept strength decay rate
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})
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```
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## Use Cases
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### 1. Story/Content Management
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```typescript
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// Create characters that evolve across chapters
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const aragornId = await vfs.createEntity({
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name: 'Aragorn',
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type: 'character',
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aliases: ['Strider', 'King Elessar'],
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attributes: { role: 'ranger', status: 'heir' }
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})
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// Track character development
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await vfs.recordAppearance(aragornId, '/chapters/01.md', 'Aragorn watched from the shadows...')
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await vfs.recordAppearance(aragornId, '/chapters/20.md', 'King Aragorn addressed his subjects...')
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// Create universal themes
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const heroJourneyId = await vfs.createConcept({
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name: 'Hero\'s Journey',
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domain: 'narrative',
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category: 'pattern',
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keywords: ['hero', 'quest', 'transformation']
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})
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```
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### 2. API Documentation That Evolves
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```typescript
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// Track API endpoints as entities
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const userApiId = await vfs.createEntity({
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name: 'Users API',
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type: 'api',
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attributes: {
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endpoints: ['/users', '/users/:id'],
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version: '1.0'
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}
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})
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// Document changes automatically
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await vfs.writeFile('/api-docs/users.md', newApiDocs) // Auto-versions if meaning changed
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await vfs.evolveEntity(userApiId, {
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attributes: { version: '1.1', endpoints: ['/users', '/users/:id', '/users/:id/profile'] }
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}, '/api-docs/users.md', 'Added profile endpoint')
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```
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### 3. Research Knowledge Management
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```typescript
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// Create research concepts
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const machineLearningId = await vfs.createConcept({
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name: 'Machine Learning',
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domain: 'ai',
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category: 'field',
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keywords: ['ML', 'artificial intelligence', 'algorithms']
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})
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// Link related concepts
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await vfs.linkConcept(machineLearningId, deepLearningId, 'contains')
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await vfs.linkConcept(machineLearningId, statisticsId, 'uses')
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// Track concept manifestations across papers
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await vfs.recordManifestation(machineLearningId, '/papers/survey.md', 'definition')
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await vfs.recordManifestation(machineLearningId, '/papers/experiment.md', 'usage')
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```
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### 4. Codebase Intelligence
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```typescript
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// Auto-extract classes and functions as entities
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const knowledge = new KnowledgeAugmentation({
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persistentEntities: { enabled: true, autoExtract: true },
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concepts: { enabled: true, autoLink: true }
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})
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// Import existing codebase
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await vfs.importFromGit('/path/to/codebase', '/project')
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// Get all extracted entities
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const entities = await vfs.findEntity({ type: 'class' })
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const functions = await vfs.findEntity({ type: 'function' })
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// Track dependencies as relationships
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const serviceId = await vfs.findEntity({ name: 'UserService' })
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const controllerEntities = await vfs.findEntityAppearances(serviceId[0].id)
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```
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## Performance Characteristics
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- **Event Recording**: 1000+ ops/second with automatic compression
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- **Semantic Versioning**: <10ms version checking with embedding cache
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- **Entity Tracking**: Handles millions of entities with graph optimization
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- **Concept System**: Sub-second similarity search across 100k+ concepts
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- **Git Bridge**: Imports 10k+ files/minute with parallel processing
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## Storage Compatibility
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Works with **ALL** Brainy storage adapters:
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- ✅ Memory (testing)
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- ✅ Redis (development)
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- ✅ PostgreSQL (production)
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- ✅ ChromaDB (vector-optimized)
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- ✅ Future adapters (only uses standard Brainy APIs)
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## Migration from Traditional VFS
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```typescript
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// Before: Basic VFS
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const vfs = new VirtualFileSystem(brain)
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// After: VFS with Knowledge Layer
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const vfs = new VirtualFileSystem(brain)
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const knowledge = new KnowledgeAugmentation()
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await knowledge.init({ brain, vfs })
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// All existing VFS methods still work exactly the same!
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await vfs.writeFile('/test.txt', 'content') // Now with intelligence
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```
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## Advanced Patterns
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### Custom Entity Extraction
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```typescript
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// Override auto-extraction with custom patterns
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class CustomEntitySystem extends PersistentEntitySystem {
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async extractEntities(filePath: string, content: Buffer): Promise<string[]> {
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// Your custom extraction logic
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const text = content.toString()
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const apiEndpoints = text.match(/app\.(get|post|put|delete)\('([^']+)'/g)
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const entityIds = []
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for (const endpoint of apiEndpoints || []) {
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const entityId = await this.createEntity({
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name: endpoint,
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type: 'endpoint',
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aliases: [],
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attributes: { method: /* extract method */, path: /* extract path */ }
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})
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entityIds.push(entityId)
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}
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return entityIds
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}
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}
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```
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### Custom Concept Detection
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```typescript
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class CustomConceptSystem extends ConceptSystem {
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async extractAndLinkConcepts(filePath: string, content: Buffer): Promise<string[]> {
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// Domain-specific concept extraction
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const text = content.toString()
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// Extract business concepts from comments
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const businessConcepts = text.match(/@business-concept:\s*([^\n]+)/g)
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const conceptIds = []
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for (const match of businessConcepts || []) {
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const conceptName = match.split(':')[1].trim()
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const conceptId = await this.createConcept({
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name: conceptName,
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domain: 'business',
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category: 'concept',
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keywords: [conceptName.toLowerCase()],
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strength: 1.0,
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metadata: { source: 'annotation' }
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})
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conceptIds.push(conceptId)
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}
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return conceptIds
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}
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}
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```
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### Event Stream Processing
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```typescript
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// Listen to all VFS events for real-time processing
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const eventRecorder = new EventRecorder(brain)
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// Custom event processor
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class RealTimeProcessor {
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async processEvent(event) {
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if (event.type === 'write' && event.path.endsWith('.md')) {
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// Process markdown files specially
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await this.extractMarkdownEntities(event.path, event.content)
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}
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}
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}
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```
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## Best Practices
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1. **Enable Gradually**: Start with basic features, enable advanced ones as needed
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2. **Tune Thresholds**: Adjust similarity/change thresholds for your domain
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3. **Custom Extraction**: Implement domain-specific entity/concept extraction
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4. **Monitor Performance**: Use built-in statistics and caching features
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5. **Version Strategy**: Consider your versioning needs when setting thresholds
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## Troubleshooting
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### Common Issues
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**Q: Too many versions being created**
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A: Increase `semanticVersioning.threshold` from 0.3 to 0.5 or higher
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**Q: Entity extraction not working**
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A: Check that `autoExtract: true` and consider custom extraction patterns
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**Q: Poor concept linking**
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A: Tune `similarityThreshold` and ensure good concept descriptions
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**Q: Slow performance**
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A: Enable caching, increase cache sizes, consider storage adapter choice
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### Debug Mode
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```typescript
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// Enable debug logging
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const knowledge = new KnowledgeAugmentation({
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// ... config
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debug: true // Logs all operations
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})
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// Check system status
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const status = knowledge.getStatus()
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console.log(status) // All subsystem states
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// Clear caches if needed
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semanticVersioning.clearCache()
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entitySystem.clearCache()
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conceptSystem.clearCache()
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```
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---
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The Knowledge Layer transforms your VFS from simple file storage into a living, breathing knowledge system. Files become intelligent, entities evolve, concepts transcend storage boundaries, and your data tells its own story.
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Welcome to the future of filesystems! 🚀 |